batch_save

async AsyncJournalTemplate.batch_save(main, body, columns=None, chunksize=1000)

批量保存日记账头和日记账体数据

参数

• main (DataFrame) – 日记账头数据Dataframe

• body (DataFrame) – 日记账体数据Dataframe

• columns (Optional[List[str]]) – 日记账头和日记账体的关联列，如提供，将以此作为日记账头和日记账体的索引，并关联组织批量保存的数据

• chunksize (int) – 保存单批次数据大小(以单行日记账头为单位)

示例

1. 初始化日记账元素

   from deepfos.element.journal_template import JournalTemplate
   jt = JournalTemplate('Journal_elimadj')
   

2. 准备日记账头和日记账体数据

   main = pd.DataFrame([
       {"journal_name": "foo", "year": "2022", "period": "1", "entity": "JH", "rate": 1},
       {"journal_name": "bar", "year": "2021", "period": "2", "entity": "JH", "rate": 2}
   ])
   
   body = pd.DataFrame([
        {"ICP": "HC", "account": "101", "rate": 1, "original_credit": 222, "credit": 222},
        {"ICP": "HCX", "account": "o1", "rate": 2, "original_credit": 111, "credit": 111},
        {"ICP": "HC", "account": "102", "rate": 1, "original_credit": 222, "credit": 222},
        {"ICP": "HCX", "account": "o2", "rate": 2, "original_credit": 111, "credit": 111}
        ]
   )
   

3. 在传入 batch_save 方法前，通过设定日记账头和日记账体的index的方式准备关联关系，然后传入 batch_save 方法

   main = main.set_index(['rate'], drop=False)
   body = body.set_index(['rate'], drop=False)
   
   jt.batch_save(main, body)
   

4. 对于关联列为相同列名时，亦可直接在 batch_save 的入参中提供列信息，将以该列信息做后续关联

   jt.batch_save(main, body, columns=['rate'])
   

5. 这两种写法在当前例子中等价

保存的batchData：

[
    JournalData(
        mainData=JournalMainData(
            mainActualTableName='main_table_actual_name',
            data={'journal_name': 'foo', 'entity': 'JH', 'period': '1', 'year': '2022'}
        ),
        bodyData=JournalBodyData(
            bodyActualTableName='body_table_actual_name',
            data=[
                {'original_credit': '222', 'account': '101', 'ICP': 'HC', 'credit': '222', 'rate': '1'},
                {'original_credit': '222', 'account': '102', 'ICP': 'HC', 'credit': '222', 'rate': '1'}
            ]
        )
    ),
    JournalData(
        mainData=JournalMainData(
            mainActualTableName='main_table_actual_name',
            data={'journal_name': 'bar', 'entity': 'JH', 'period': '2', 'year': '2021'}
        ),
        bodyData=JournalBodyData(
            bodyActualTableName='body_table_actual_name',
            data=[
                {'original_credit': '111', 'account': 'o1', 'ICP': 'HCX', 'credit': '111', 'rate': '2'},
                {'original_credit': '111', 'account': 'o2', 'ICP': 'HCX', 'credit': '111', 'rate': '2'}
            ]
        )
    )
]